UnknownNot Applicable

SVP Detection Using Machine Learning

United Kingdom210 participantsStarted 2023-03-01

Plain-language summary

This diagnostic study will use 410 retrospectively captured fundal videos to develop ML systems that detect SVPs and quantify ICP. The ground truth will be generated from the annotations of two independent, masked clinicians, with arbitration by an ophthalmology consultant in cases of disagreement.

Who can participate

Age range18 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: * Patients aged ≥18 years with presumed normal ICP undergoing routine dilated OCT scans. * Patients undergoing a LP or continuous ICP monitoring with implanted transcranial pressure transducer devices at in- or out-patient neurology, neurosurgery or neuro-ophthalmology services. Exclusion Criteria: * Glaucoma diagnosis or glaucoma suspects in either eye. * Bilateral restricted fundal view, e.g. advanced bilateral cataracts. * Bilateral retinal vein or artery occlusion.

What they're measuring

Area-under-the receiver operating characteristic (AUROC) for spontaneous venous pulsations detection

Timeframe: 1 year

Trial details

NCT IDNCT05731765

SponsorKing's College London

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2024-11

View on ClinicalTrials.gov More Intracranial Pressure Increase trials